| | ---
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| | library_name: transformers
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| | language:
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| | - de
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| | license: apache-2.0
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| | base_model: openai/whisper-small
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| | tags:
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| | - generated_from_trainer
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| | datasets:
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| | - PolyAI/minds14
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| | metrics:
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| | - wer
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| | model-index:
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| | - name: Whisper Small de
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| | results:
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| | - task:
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| | name: Automatic Speech Recognition
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| | type: automatic-speech-recognition
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| | dataset:
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| | name: minds14
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| | type: PolyAI/minds14
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| | metrics:
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| | - name: Wer
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| | type: wer
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| | value: 15.885206143896525
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| | ---
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| |
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| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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| | should probably proofread and complete it, then remove this comment. -->
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| |
|
| | # Whisper Small de
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| |
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| | This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the minds14 dataset.
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| | It achieves the following results on the evaluation set:
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| | - Loss: 0.5515
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| | - Wer Ortho: 17.4089
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| | - Wer: 15.8852
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| |
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| | ## Model description
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| |
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| | More information needed
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| |
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| | ## Intended uses & limitations
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| |
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| | More information needed
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| |
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| | ## Training and evaluation data
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| |
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| | More information needed
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| |
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| | ## Training procedure
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| |
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| | ### Training hyperparameters
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| |
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| | The following hyperparameters were used during training:
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| | - learning_rate: 1e-05
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| | - train_batch_size: 16
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| | - eval_batch_size: 16
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| | - seed: 42
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| | - optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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| | - lr_scheduler_type: constant_with_warmup
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| | - lr_scheduler_warmup_steps: 50
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| | - training_steps: 500
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| | - mixed_precision_training: Native AMP
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| |
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| | ### Training results
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| |
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| | | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
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| | |:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
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| | | 0.0015 | 16.1290 | 500 | 0.5515 | 17.4089 | 15.8852 |
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| |
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| |
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| | ### Framework versions
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| |
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| | - Transformers 4.55.0
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| | - Pytorch 2.8.0+cu126
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| | - Datasets 3.6.0
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| | - Tokenizers 0.21.4
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| |
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